Abstract
Bead-on-plate welds were carried out on aluminum plates Al-1100 using an electron beam welding machine. The weld runs were conducted as per central composite design. Regression analysis was then carried out to establish input–output relationships of the process. The weldment area was minimized, after satisfying the condition of maximum bead penetration. The above constrained optimization problem was solved utilizing a genetic algorithm (GA) with a penalty function approach. The GA was able to determine optimal weld-bead geometry and recommend the necessary process parameters for the same. An attempt was also made to model the complicated dagger-like profile of electron-beam welded material by utilizing three third-order curves. The profiles were predicted by utilizing both back-propagation trained and GA-tuned neural networks. The latter was able to yield better predictions compared to the former.
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Dey, V., Pratihar, D.K., Datta, G.L. et al. Optimization and prediction of weldment profile in bead-on-plate welding of Al-1100 plates using electron beam. Int J Adv Manuf Technol 48, 513–528 (2010). https://doi.org/10.1007/s00170-009-2307-1
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DOI: https://doi.org/10.1007/s00170-009-2307-1